A media resource server (MRS) in the field of telecommunications generally provides media resources such as playback, recording, and double tone multiple frequency (DTMF) detection resources to realize interactive voice response (IVR) service functions and provides conference audio mixing resources to realize service functions associated with teleconference. Plenty of audio codec resources are allocated on the MRS to facilitate the multiple access of user terminals to the MRS at the same time. Besides, the codec supports various algorithm formats to cater to different media formats at the user terminals (for example, G.711 and G.729). Referring to FIG. 1, if an encoding format of a playback file is not consistent with a format at the user terminal, a playback decoder decodes an audio file on a local file server, then encodes the file into the format supported by the user terminal, and sends the encoded file to the user terminal. When an encoding format of speech data input by the user terminal to the MRS is not consistent with a format of a recording file, the input speech data is first decoded, then encoded into a format consistent with that of the recording file, and then stored in the local file server. The DTMF detection is adapted to detect a DTMF number dialed by a user after the input speech data is decoded, and implement subsequent service functions according to different DTMF numbers.
The media resources such as encoders, decoders, and DTMF detection resources are usually provided by a distributed media processing equipment (for example, a DSP typically) group. Each media processing equipment group includes more than one media processing equipment, and each media processing equipment is allocated with a certain number of media resources, including audio encoders, audio decoders, and DTMF detections, which are combined together to realize various functions associated with media services.
With the rapid development of communication services, the MRS is required to support more and more types of media resources, so that various types of media resources need to be integrated in single media processing equipment. Under the conditions of a set algorithm complexity of audio algorithm formats (indicated by MCPS: megacycles per second, an index adapted to measure a processor capability and an algorithm complexity) and a selected media processing equipment, how to employ a preferred resource management and allocation solution to fully utilize the media processing equipment resources to improve the channel density of a single media processing equipment group plays a critical role in achieving the purposes of saving the cost and enhancing the product competitiveness.
A resource management method in the conventional art is to bind encoding resources and decoding resources of the same audio algorithm for unified management. The algorithm complexity varies among different audio algorithm formats, and the number of channel resources (encoding resources+decoding resources) supported by one media processing equipment is calculated according to an audio algorithm format with the highest algorithm complexity. Specifically, an audio algorithm supporting three types of formats is taken as an example, among which the algorithm complexity of an algorithm format A is x, the algorithm complexity of an algorithm format B is y, and the algorithm complexity of an algorithm format C is z, x<y<z. If the available processing capability of one media processing equipment is P, the number of channel resources supported by the media processing equipment is P/z. Though the algorithm complexity x of the algorithm format A is lower than the algorithm complexity z of the algorithm format C, the number of channel resources supported by one media processing equipment in the algorithm format A can only be P/z. It is assumed that the resources allocated to one media processing equipment are all in the algorithm format A, and the actually wasted processing capability of the equipment is P−x*(P/z). Taking actual data for example, the algorithm complexity of the algorithm format A is 2 MCPS, the algorithm complexity of the algorithm format B is 4 MCPS, the algorithm complexity of the algorithm format C is 5 MCPS, and the available processing capability of one media processing equipment is 500 MCPS, so that the number of channel resources supported by one media processing equipment is 500/5=100 according to the conventional art. That is to say, even if the media processing equipment is only provided with the algorithm format A, the largest number of channel resources supported by the equipment is still 100. In contrast, theoretically, the largest number of channel resources supported by one media processing equipment in the algorithm format A is 500/2=250.
Meanwhile, in the media resource management method of the conventional art, the encoding resources and the decoding resources of the same audio format are bound, and a digital signal codec channel is opened to correspond to the user during call accessing or service processing. In practice, the encoding resources and the decoding resources required by many services are not symmetrical, so that the allocation of encoding and decoding resources at the same time may cause severe waste of resources. What's worse, if the DTMF detection resources are further taken into account, the algorithm complexity of the DTMF detection resources also needs to be considered in the algorithm complexity of the channel calculation. In actual applications, the encoding/decoding resources, for example, playback decoding resources, adopted by some services do not need DTMF detection resources, so that the above method may further cause severe waste of media resources.
In view of the above, the resource management and allocation method provided in the conventional art results in serious waste of media resources.